Academic Journals Database
Disseminating quality controlled scientific knowledge

Indoor versus Outdoor Scene Classification Using Probabilistic Neural Network

Author(s): Gupta Lalit | Pathangay Vinod | Patra Arpita | Dyana A | Das Sukhendu

Journal: EURASIP Journal on Advances in Signal Processing
ISSN 1687-6172

Volume: 2007;
Issue: 1;
Start page: 094298;
Date: 2007;
Original page

We propose a method for indoor versus outdoor scene classification using a probabilistic neural network (PNN). The scene is initially segmented (unsupervised) using fuzzy -means clustering (FCM) and features based on color, texture, and shape are extracted from each of the image segments. The image is thus represented by a feature set, with a separate feature vector for each image segment. As the number of segments differs from one scene to another, the feature set representation of the scene is of varying dimension. Therefore a modified PNN is used for classifying the variable dimension feature sets. The proposed technique is evaluated on two databases: IITM-SCID2 (scene classification image database) and that used by Payne and Singh in 2005. The performance of different feature combinations is compared using the modified PNN.
Affiliate Program      Why do you need a reservation system?